Identifying Subway Passenger Flow under Large-Scale Events Using Symbolic Aggregate Approximation Algorithm

2021 ◽  
pp. 036119812110478
Author(s):  
Hainan Huang ◽  
Rongjie Zhang ◽  
Chengguang Xie ◽  
Xiaofeng Li
Keyword(s):  
Large Scale ◽  
Urban Rail Transit ◽  
Sporting Events ◽  
Transit Systems ◽  
Symbolic Aggregate Approximation ◽  
Social Events ◽  
Urban Rail ◽  
Subway System ◽  
Passenger Flows ◽  
Dynamic Time

Various social events, such as holidays, important sporting events, and major celebrations, may result in sudden large-scale passenger flows in certain sections and stations of urban rail transit systems. The sudden inbound passenger flows caused by these events can easily lead to continuous congestion of the subway network, which has a profound impact on the safety, reliability, and stability of a subway system. Because of the large magnitude of swipe data and the high dimensionality of time series, it is difficult to identify the emergence of such large passenger flows. Additionally, the recognition accuracy of the existing identification methods cannot meet the operational monitoring requirements. To address the above-mentioned issues, this paper proposes an optimized symbolic aggregate approximation (SAX) algorithm to identify historical sudden passenger flows caused by large-scale events around subways. Specifically, pre-set cluster types and dynamic time warping (DTW) are proposed to enhance the matching rate. Compared with the K-means method, the proposed method exhibits an average increase of 30% in mining accuracy, and the calculation time is shortened to one-sixteenth of the original value.

scholarly journals Demand Analysis and Distribution of Single-Trip Ticket Cards for Urban Rail Transit

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zi-jia Wang ◽  
Jing-qi Li ◽  
Jiang-yue Wu ◽  
Zhi-gang Yang
Keyword(s):  
Urban Rail Transit ◽  
Distribution Model ◽  
Rail Transit ◽  
Effective Management ◽  
Transit Systems ◽  
Urban Rail ◽  
Usage Patterns ◽  
Subway System ◽  
Loading And Unloading ◽  
Hybrid Distribution

In the current urban rail transit systems, nearly 15% of passengers are noncommuter travelers who use single-trip ticket cards (ticket cards). Accordingly, the effective management of ticket cards is of great importance. This article suggests a time series model for use in predicting ticket card storage based on the characteristics of ticket cards collected by an automatic fare collection (AFC) system. The distribution cycle, station types, and distribution volume of each station are also determined. Then, drawing on small package transportation feasibility theory, an unbalanced distribution model between production and demand (unbalanced distribution model), as well as a hybrid distribution model of loading and unloading (hybrid distribution model), is established. Application of these models to the Beijing Subway system is used to verify the efficiency and feasibility of such a hybrid distribution model. The analysis and results offer insights into usage patterns of urban rail transit ticket cards, providing solid evidence for a relative decision-making process.

scholarly journals Dynamic Disruption Simulation in Large-Scale Urban Rail Transit Systems

2019 ◽  
pp. 129-140
Author(s):  
Steffen O. P. Blume ◽  
Michel-Alexandre Cardin ◽  
Giovanni Sansavini
Keyword(s):  
Large Scale ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Systems ◽  
Urban Rail

scholarly journals Research on Passenger Flow Early Warning of Urban Rail Transit Station Based on System Dynamics

2020 ◽  
Vol 308 ◽  
pp. 01003
Author(s):  
Hui Chen ◽  
Bo Wang ◽  
Wei He ◽  
Jianhu Zheng
Keyword(s):  
System Dynamics ◽  
Early Warning ◽  
Large Scale ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Flows ◽  
Transit Station ◽  
The Impact

Large-scale passenger flows occur frequently during the peak hours of urban rail transit stations and on holidays. Thus, the timely and accurate early warning of impending large-scale passenger flows can positively impact the operational safety of the entire station. By further deepening the definition of passenger flow warnings in stations, a new model of urban rail transit station passenger flow based on system dynamics is constructed. The method of determining the key area of passenger flows in the early warning stage based on streamlines is proposed; the key indicators and thresholds affecting early warnings are studied. Finally, taking a typical station as an example, a station model is built using Anylogic software. The parameter sensitivity analysis is used to determine the impact of each key indicator on the passenger flow in the key area of the station early warning, and the reference threshold of each indicator is determined.

Research on Hyperpaths in the Urban Rail Transit Network

2014 ◽  
Vol 488-489 ◽  
pp. 1439-1443
Author(s):  
Jin Hai Li ◽  
Jian Feng Liu
Keyword(s):  
Large Scale ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Network ◽  
Travel Costs ◽  
Urban Rail ◽  
Distinctive Structure ◽  
Feasible Path ◽  
Definition Of ◽  
Urban Rail Transit Network

Hyperpaths enumeration is one of the basic procedures in many traffic planning issues. As a result of its distinctive structure, hyperpaths in Urban Rail Transit Network (URTN) are different from those in road network. Typically, one may never visit a station more than once and would never transfer from one line to another that has been visited in a loopless URTN, meaning that stations a hyperpath traversed cannot be repeated, neither do lines in loopless networks. This paper studies the relationships between feasible path and the shortest path in terms of travel costs. In this paper, a new definition of hyperpath in URTN is proposed and a new algorithm based on the breadth first searching (BFS) method is presented to enumerate the hyperpaths. The algorithm can safely avoid hyperpath omission and can even be applied in networks containing loops as well. The influence of parameters on hyperpaths is studied by experimentally finding hyperpaths in the subway network in Beijing. A group of suggested parameter pairs are then given. Finally, a numerical experiment is used to illustrate the validity of the proposed algorithm. The results imply the significance of the convergence of the BFS algorithm which can be used to search hyperpaths in large scale URTN even with loop.

scholarly journals Overview of Anti-Seismic Researches of Underground Structures

2018 ◽  
Vol 38 ◽  
pp. 03038
Author(s):  
Ran Liao
Keyword(s):  
Research Methods ◽  
Underground Structure ◽  
Seismic Damage ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Underground Structures ◽  
Transit System ◽  
Urban Rail ◽  
Subway System ◽  
Metro System

With the vigorous development of urban rail transit system, especially the construction of subway system, the safety of subway system draws more and more attention. The study of anti-seismic for underground structures has also become an important problem to be solved in the construction of Metro system. Based on the typical underground structure seismic damage phenomenon, this paper summarizes the seismic characteristics, research methods and design methods of underground structures to offer a guide for engineers.

scholarly journals Energy-Efficient Train Driving Strategy with Considering the Steep Downhill Segment

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 77 ◽  
Author(s):  
Wentao Liu ◽  
Tao Tang ◽  
Shuai Su ◽  
Jiateng Yin ◽  
Yuan Cao ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Solution Space ◽  
Descent Method ◽  
Urban Rail Transit ◽  
Gradient Descent Method ◽  
Transit Systems ◽  
Classical Energy ◽  
Urban Rail ◽  
Save Energy

Implementation of energy-efficient train driving strategy is an effective method to save train traction energy consumption, which has attracted much attention from both researchers and practitioners in recent years. Reducing the unnecessary braking during the journey and increasing the coasting distance are efficient to save energy in urban rail transit systems. In the steep downhill segment, the train speed will continue to increase without applying traction due to the ramp force. A high initial speed before stepping into the steep downhill segment will bring partial braking to prevent trains from overspeeding. Optimization of the driving strategy of urban rail trains can avoid the partial braking such that the potential energy is efficiently used and the traction energy is reduced. This paper presents an energy-efficient driving strategy optimization model for the segment with the steep downhill slopes. A numerical method is proposed to calculate the corresponding energy-efficient driving strategy of trains. Specifically, the steep downhill segment in the line is identified firstly for a given line and the solution space with different scenarios is analyzed. With the given cruising speed, a primary driving strategy is obtained, based on which the local driving strategy in the steep slope segment is optimized by replacing the cruising regime with coasting regime. Then, the adaptive gradient descent method is adopted to solve the optimal cruising speed corresponding to the minimum traction energy consumption of the train. Some case studies were conducted and the effectiveness of the algorithm was verified by comparing the energy-saving performance with the classical energy-efficient driving strategy of “Maximum traction–Cruising–Coasting–Maximum braking”.

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